Automation of main tasks for movement such as transportation, circulation, and inspection work of baggage is expected. It is important to autonomously move a robot to automate such tasks. Under a general environment in which circumstances around a robot change over time, it may be difficult to cope with dynamic obstacles and quasi-static obstacles during autonomous movement.
For example, autonomous performance is enhanced by utilizing external information such as Global Positioning System (GPS) position information and detailed road map information provided by a car navigation system or the like during automatic running of a vehicle. Robots for in-facility and indoor movement, for which support based on the above-described external information cannot be expected, are required to acquire a movement map for controlling movement. Thus, there is a possibility that a degree of difficulty of autonomy of movement will be high.
Navigation accuracy is expected to be improved by adopting map composition technology such as simultaneous localization and mapping (SLAM) during autonomous movement. However, map updating and matching processes cannot keep up with a rapidly changing dynamic surrounding environment. Therefore, there is a possibility of a failure in self-position recognition and path generation.
As a method of coping with a change in topography, for example, a change in an existence state of an obstacle around a robot, it is conceivable for a certainty factor (existence accuracy) to be updated with a grid map. Thus, it is possible to reduce an influence of noise (sensor noise) mixed in a signal detected by a sensor and improve the accuracy of position recognition. However, because information set in the grid map is merely modified, it is difficult to cope with a dynamic environment in which obstacles that change significantly with time exist. For example, if a threshold value for reliability is lowered, information about a map to be referred to may be disturbed due to noise such as dynamic obstacles. On the other hand, if the threshold value is increased, it may not be possible to cope with a case in which an environment actually changes.